20 results about "Language disorder" patented technology

The invention relates to the technical field of language barrier evaluation, and discloses a deep learning-based language barrier executive intervention effect evaluation method. The method comprises the following steps: acquiring real-time voice data and facial expression data of a language barrier patient in intervention training through a multi-modal data acquisition device to form an original behavior feature set; performing acoustic feature hierarchical analysis on the voice data by adopting a time sequence feature extraction network to generate a voice time sequence feature vector; performing micro-expression dynamic capture on the expression data through a three-dimensional convolutional neural network to generate an expression state feature vector; inputting the two types of vectors into a multi-modal feature fusion layer to carry out cross-modal correlation analysis, and generating a comprehensive behavior evaluation matrix; on the basis of the matrix, an intervention effect analysis model driven by an attention mechanism is adopted, a behavior improvement degree index of the current intervention stage is calculated, accurate evaluation of the intervention effect is achieved, and support is provided for dynamic adjustment of language barrier rehabilitation intervention.

A method for treating a language disorder in a patient includes receiving therapist input specifying a speech target and engagement indicator priority, capturing audio of a speech response to a therapy prompt, and identifying the language of the response using a multilingual language identification model. The method further comprises analyzing the speech response with a language-specific recognition model to extract speech features and classify errors across multiple linguistic and acoustic dimensions. Engagement indicators are extracted and used to compute an engagement score, which, along with the error classifications and speech target, informs a decision model that selects a therapy task. The selected task is presented to the patient, and a subsequent speech response is captured to update error classifications. The decision model is iteratively refined based on therapist input and revised error data, enabling adaptive, personalized therapy progression.

The invention discloses a big language model security test method and system based on a small language cross-language attack. The method comprises the steps of constructing a small language selection strategy library, designing a cross-language semantic conversion engine, constructing a multi-dimensional language barrier, implementing a self-adaptive language switching mechanism and establishing a cross-language security evaluation system. According to the method, through dual language barriers of minority language input and Chinese output, a traditional single-language security detection system is effectively bypassed, attack content is presented in a minority language form, but a target model is forced to reply with Chinese, and a language understanding gap is established between input and output; the dynamic language switching strategy realizes intelligent cross-language attack, and the attack method can be adjusted in real time according to the defense response of the target model. According to the method, the adaptability, the concealment and the overall test effect of attacks are remarkably improved, and a systematized and efficient technical means is provided for large model security assessment in a multi-language environment.

The application relates to a development language disorder early identification method and system fusing neural activity features and belongs to the technical field of artificial intelligence. The method comprises the following steps: acquiring original neurophysiological signals and matched clinical information, and constructing a data set; power features and coherence features of the signals are normalized to generate enhanced feature vectors; attention weighted feature vectors are obtained through mutual information based attention mechanism weighting; the radial basis function is used to nonlinearly map the feature vectors to a high-dimensional space to obtain extended feature vectors; a development language disorder early identification model is constructed, brain region level feature aggregation and modulation, clinical factor fusion and gate modulation are adopted, a decision function fusing nonlinear interaction items is introduced, and a binary cross entropy loss function is used to optimize the model; after model training is completed by using a training set, signals of a subject to be evaluated are input into the model after the same preprocessing, and an identification result is output. The application can improve the accuracy of development language disorder early identification.

According to an embodiment, a device for script extraction and subtitle transmission synchronized with live performing art content is provided. When a viewer views verbal performing arts such as plays or musicals, the device projects commentary subtitles synchronized in real time with performance content in a preferred language in front of eyes by using a display device including AR smart subtitle glasses, in order to eliminate a language barrier due to nationality or an auditory barrier caused by hearing impairment or hearing loss and enable viewing of the performing arts, so that the subtitles can be viewed in synchronization with the performance.

The invention discloses an adaptive bilingual scientific education content intelligent recommendation system, which belongs to the technical field of intelligent education recommendation systems, is particularly suitable for primary school multi-language background students, and comprises a learner model construction engine, a multi-language resource matching module, a learning path optimization module, a content difficulty adjustment module and a teacher support module. The scientific concept understanding degree and the language proficiency degree of students are subjected to two-dimensional modeling, the bilingual content proportion is dynamically adjusted based on a language ability self-adaptive weighting strategy, scientific knowledge acquisition and language ability development goals are collaboratively optimized, a personalized bilingual learning path is generated, and actual deployment shows that the system enables the scientific score to be improved by 32%, the English vocabulary amount to be increased by 45% and the learning efficiency to be improved by 30%. The influence of language barriers on scientific learning is effectively solved, and the dual purposes of scientific education and language education are achieved.

1. Name of the product in this design: Speech Communication Assistive Training Device. 2. Purpose of this design: To provide speech training or assist communication for people with language impairments. 3. The key design feature of this product is its shape. 4. The image or photograph that best illustrates the design's key points: 3D view 1.

The invention relates to a neural activity feature fused developmental language disorder early recognition method and system, and belongs to the technical field of artificial intelligence. The method comprises the following steps: acquiring an original neurophysiological signal and matched clinical information, and constructing a data set; performing normalization processing on the power feature and the coherence feature of the signal to generate an enhanced feature vector; obtaining an attention weighted feature vector through attention mechanism weighting based on mutual information; performing nonlinear mapping to a high-dimensional space by using a radial basis function to obtain an extended feature vector; the method comprises the following steps: constructing a developmental language disorder early recognition model, introducing a decision function fused with a nonlinear interaction item by adopting brain region level feature aggregation and modulation, clinical factor fusion and gating modulation, and optimizing the model by a binary cross entropy loss function; and after model training is completed by using the training set, inputting a to-be-evaluated tested signal into the model after same preprocessing, and outputting an identification result. According to the invention, the accuracy of early recognition of the developmental language barrier can be improved.

The invention discloses a language disorder assessment method and system, and belongs to the technical field of data processing, and the method comprises the steps that a user side accesses a language assessment platform, a language cognition task is generated, the language cognition task comprises a main language task and a secondary cognition task, and task sequence generation is carried out with cognition load increase; issuing the language cognition task to a user side thread, executing a task language test, and returning a task language flow; and a cognitive evaluation module embedded in the language evaluation platform is triggered, cascade evaluation based on logic paradox, language entropy change and a high-dimensional semantic network is executed, a language evaluation result is generated, and popup window display is performed on a platform user side. According to the method and the device, the technical problem that potential or slight language barriers are difficult to effectively induce and detect due to single language evaluation environment and lack of cognitive pressure in the prior art is solved.

Pharmacological methods and single unit dosage forms for treating the expressive language deficit in an autistic human child or adult are provided. A therapeutically effective dose of enantiomerically enriched R-ethosuximide or a pharmaceutically acceptable salt thereof is administered to a patient suffering from expressive language deficit, preferably over an extended period, e.g., six months or longer, to reduce the autistic patient's expressive language deficit.

The invention discloses a psychological health coach voice model optimization method based on large language model driving, and the method employs a voice signal preprocessing module, a multi-modal emotion feature extraction module, a dynamic weight distribution module, a large language model reasoning module, a voice synthesis optimization module, and a hardware cooperation acceleration module which are sequentially connected in series through a data bus. The dynamic weight distribution module is in two-way communication with the multi-modal emotion feature extraction module and the large language model reasoning module, and the hardware collaborative acceleration module is in parallel connection with the large language model reasoning module through a PCIe channel; according to the invention, through the multi-modal feature fusion (voice, text and micro-expression) and dynamic weight distribution technology, the emotion recognition precision is obviously improved, and the complex emotion state of a user is effectively captured; the dialect self-adaption unit breaks through regional language barriers through accent conversion mapping, and the dialect user interaction effectiveness is improved.

1. The name of the design product: language development disorder brain magnetic diagnostic instrument. 2. The use of the design product: application instrument for diagnosing autism and other language disorder children. 3. The design points of the design product: in shape. 4. The picture or photo that best indicates the design points: perspective view. 5. The bottom of the design product is not easy to see or not visible during use, omit the top view.

The invention belongs to the technical field of equipment control, and particularly relates to a wearable equipment control method and system based on AI vision and behavior prediction, and the method comprises the steps: obtaining intelligent wearable equipment data, and carrying out the preprocessing; allocating a pseudo name identifier to the multi-modal feature set, and constructing a time sequence causal chain of the perception data and the behavior intention; generating a lightweight model according to the intention probability distribution, and pre-generating a voice feedback text by event driving; a mapping model is trained according to the voice feedback instruction set and the head micro-deformation signal, and a control instruction is generated through matching; updating visual, auditory and language AI models through federal learning; and according to the optimized AI model and the labeled field data, generating a pseudo tag adaptation model through neighbor semi-supervision, and outputting a wearable device control scheme. The AI + AR technology integrates the four functions of vision, hearing, language and brain power, and the problems of life self-care and social communication pain points of people suffering from vision, hearing and language disorders and mild cerebral palsy are solved.

A pharmacological method for treating the expressive language deficit in an autistic human child or adult is provided. A therapeutically effective dose of a succinimide anticonvulsant, e.g., ethosuximide, methsuximide, phensuximide, or a pharmaceutically acceptable salt thereof, is administered to a patient suffering from expressive language deficit, preferably over an extended period, e.g., six months or longer. Language gains are retained even after treatment is discontinued.

This application relates to the field of voice interaction technology, and in particular to a voice recognition enhancement method and system for patients with chronic diseases. The method includes: acquiring a voice information set of target Alzheimer's patients; analyzing the ambiguous semantics and potential intentions of the voice information under disease-related language impairments based on the voice information set to obtain an intention hypothesis information set; acquiring an interaction flow dataset; analyzing the joint confidence of each intention based on the interaction flow dataset and the intention hypothesis information set, and proceeding to direct intention confirmation or multimodal assisted intention confirmation according to the joint confidence to obtain a deterministic intention information set; analyzing the decay information of semantic mapping relationships based on the deterministic intention information set, updating the personalized dynamic semantic map corresponding to the patient, retrieving the personalized dynamic semantic map based on the patient's real-time voice information, generating and outputting care warning information, and recording a voice recognition enhancement log. This improves the patient's quality of life and safety.

The invention discloses a Tibetan dialect protection and real-time cross-dialect translation system based on voiceprint recognition, and relates to the technical field of voice processing, the Tibetan dialect protection and real-time cross-dialect translation system comprises a voiceprint recognition module, a voice recognition module, a cross-dialect translation module, a voice synthesis module and a safety and audit module, the speech recognition module writes an input dialect speech stream into a standard Tibetan text according to a judged dialect category, the cross-dialect translation module receives the Tibetan text and drives a Tibetan large language model to complete semantic conversion and text generation, and the speech synthesis module converts the dialect text into target Tibetan dialect speech. According to the method, voiceprint recognition and dialect classification are combined, so that the function of personalized accurate cross-dialect translation is realized, the problem of difficult communication caused by large difference of Tibetan dialects is effectively solved, users of different dialects can perform smooth and natural real-time dialogues, and language barriers are broken through.

Pharmacological methods and single unit dosage forms for treating the expressive language deficit in an autistic human child or adult are provided. A therapeutically effective dose of enantiomerically enriched R-ethosuximide or a pharmaceutically acceptable salt thereof is administered to a patient suffering from expressive language deficit, preferably over an extended period, e.g., six months or longer, to reduce the autistic patient's expressive language deficit.

The invention relates to the technical field of pediatric language impairment, the course further comprises a language cognition first order, a language and cognition middle order and a language cognition high order, the language cognition first order comprises a foundation and language and communication, the language cognition high order comprises a learning foundation, language and communication, games and sociality, and the foundation comprises the following steps: S1, learning the foundation; according to the technical scheme, in the training process, parents can timely give forward strengthening, such as prying and encouraging, which is very important for children to establish confidence and overcome language barriers, and in the natural family environment, the parents can integrate training into specific situations in daily life, so that the training efficiency is improved. Language skill learning and application are more vivid and natural, communication and interaction between parents and children can be enhanced by jointly participating in the language training process, the language skill of the children can be improved, and meanwhile the emotional relation between the parents and the children can be improved.

1. Name of the product in this design: Language Disorder Rehabilitation Assessment and Training System. 2. Purpose of this design: To assist in the training of patients with mild speech impairment caused by stroke. 3. The key design feature of this product is its shape. 4. The image or photograph that best illustrates the design's key points: a 3D model.